The official PyTorch implementation for the paper "sMGC: A Complex-Valued Graph Convolutional Network via Magnetic Laplacian for Directed Graphs".

Related tags

Deep Learningpython3pytorchlaplaciangnndigraphs
Overview

Magnetic Graph Convolutional Networks

The Magnetic Eigenmap

A directed 4-cycle

About

The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via Magnetic Laplacian for Directed Graphs.

Requirements

To install requirements:

pip3 install -r requirements.txt

Results

Node classification accuracy in Citation networks (%)

Model CoRA CiteSeer PubMed
GAT 82.60 ± 0.40 70.45 ± 0.25 77.45 ± 0.45
sMGC 82.70 ± 0.00 73.30 ± 0.00 79.90 ± 0.10
MGC 82.50 ± 1.00 71.25 ± 0.95 79.70 ± 0.40

Node classification accuracy in WebKB (%)

Model Cornell Texas Washington Wisconsin
GAT 41.03 ± 0.00 52.63 ± 2.63 63.04 ± 0.00 56.61 ± 1.88
sMGC 73.08 ± 1.28 71.05 ± 0.00 68.48 ± 3.26 80.19 ± 2.83
MGC 80.77 ± 3.85 82.90 ± 1.31 70.66 ± 1.08 87.74 ± 2.83

Reproduce experiment results

sMGC

CoRA:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/cora.ini' --alpha=0.03 --t=8.05 --K=38

CiteSeer:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/citeseer.ini' --alpha=0.01 --t=5.16 --K=40

PubMed:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/pubmed.ini' --alpha=0.01 --t=5.95 --K=25

Cornell:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/cornell.ini' --alpha=0.95 --t=45.32 --K=12

Texas:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/texas.ini' --alpha=0.71 --t=45.08 --K=23

Washington:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/washington.ini' --alpha=0.77 --t=45.95 --K=44

Wisconsin:

python3 main_smgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/wisconsin.ini' --alpha=0.93 --t=25.76 --K=34

MGC

CoRA:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/cora.ini' --alpha=0.08 --t=5.85 --K=10 --droprate=0.4

CiteSeer:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/citeseer.ini' --alpha=0.01 --t=25.95 --K=35 --droprate=0.3

PubMed:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/pubmed.ini' --alpha=0.03 --t=15.95 --K=20 --droprate=0.5

Cornell:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/cornell.ini' --alpha=0.66 --t=38.49 --K=31 --droprate=0.6

Texas:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/texas.ini' --alpha=0.75 --t=0.53 --K=4 --droprate=0.5

Washington:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/washington.ini' --alpha=0.73 --t=42.36 --K=21 --droprate=0.1

Wisconsin:

python3 main_mgc.py --mode='test' --seed=100 --dataset_config_path='./config/data/wisconsin.ini' --alpha=0.34 --t=0.52 --K=12 --droprate=0.5
Owner
What we know is a drop. What we do not know is an ocean.
GitHub Repository
Fedlearn支持前沿算法研发的Python工具库 | Fedlearn algorithm toolkit for researchers

FedLearn-algo Installation Development Environment Checklist python3 (3.6 or 3.7) is required. To configure and check the development environment is c

89 Nov 14, 2022
Utilities to bridge Canvas-generated course rosters with GitLab's API.

gitlab-canvas-utils A collection of scripts originally written for CSE 13S. Oversees everything from GitLab course group creation, student repository

Eugene Chou 5 Jun 08, 2022
I will implement Fastai in each projects present in this repository.

DEEP LEARNING FOR CODERS WITH FASTAI AND PYTORCH The repository contains a list of the projects which I have worked on while reading the book Deep Lea

Thinam Tamang 43 Dec 20, 2022
Official implementation of "Open-set Label Noise Can Improve Robustness Against Inherent Label Noise" (NeurIPS 2021)

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise NeurIPS 2021: This repository is the official implementation of ODNL. Require

Hongxin Wei 12 Dec 07, 2022
Auto White-Balance Correction for Mixed-Illuminant Scenes

Auto White-Balance Correction for Mixed-Illuminant Scenes Mahmoud Afifi, Marcus A. Brubaker, and Michael S. Brown York University Video Reference code

Mahmoud Afifi 47 Nov 26, 2022
The 2nd place solution of 2021 google landmark retrieval on kaggle.

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

229 Dec 13, 2022
Framework web SnakeServer.

SnakeServer - Framework Web 🐍 Documentação oficial do framework SnakeServer. Conteúdo Sobre Como contribuir Enviar relatórios de segurança Pull reque

Jaedson Silva 0 Jul 21, 2022
Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.

Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the

Alex Taradachuk 2 Aug 07, 2022
Single-stage Keypoint-based Category-level Object Pose Estimation from an RGB Image

CenterPose Overview This repository is the official implementation of the paper "Single-stage Keypoint-based Category-level Object Pose Estimation fro

NVIDIA Research Projects 188 Dec 27, 2022
Towards Debiasing NLU Models from Unknown Biases

Towards Debiasing NLU Models from Unknown Biases Abstract: NLU models often exploit biased features to achieve high dataset-specific performance witho

Ubiquitous Knowledge Processing Lab 22 Jun 14, 2022
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)

Benedek Rozemberczki 393 Dec 13, 2022
Code for Fully Context-Aware Image Inpainting with a Learned Semantic Pyramid

SPN: Fully Context-Aware Image Inpainting with a Learned Semantic Pyramid Code for Fully Context-Aware Image Inpainting with a Learned Semantic Pyrami

12 Jun 27, 2022
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

mani 1.2k Jan 07, 2023
Covid19-Forecasting - An interactive website that tracks, models and predicts COVID-19 Cases

Covid-Tracker This is an interactive website that tracks, models and predicts CO

Adam Lahmadi 1 Feb 01, 2022
Image inpainting using Gaussian Mixture Models

dmfa_inpainting Source code for: MisConv: Convolutional Neural Networks for Missing Data (to be published at WACV 2022) Estimating conditional density

Marcin Przewięźlikowski 8 Oct 09, 2022
Gym for multi-agent reinforcement learning

PettingZoo is a Python library for conducting research in multi-agent reinforcement learning, akin to a multi-agent version of Gym. Our website, with

Farama Foundation 1.6k Jan 09, 2023
[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

Xiefan Guo 122 Dec 11, 2022
Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

1 Jun 02, 2022
Cross View SLAM

Cross View SLAM This is the associated code and dataset repository for our paper I. D. Miller et al., "Any Way You Look at It: Semantic Crossview Loca

Ian D. Miller 99 Dec 09, 2022
Unofficial PyTorch Implementation of Multi-Singer

Multi-Singer Unofficial PyTorch Implementation of Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus. Requirements See re

SunMail-hub 123 Dec 28, 2022